Battery data feature processing method, device and platform and storage medium

Abstract

The invention discloses a battery data feature processing method, device and platform and a storage medium, and belongs to the technical field of data processing. The method comprises the steps of obtaining to-be-processed battery data representing a battery operation condition; calling a corresponding configuration rule based on the to-be-processed battery data, wherein the configuration rule is used for performing feature processing on the to-be-processed battery data; and performing feature processing on the to-be-processed battery data through the configuration rule to obtain a processing result, and performing feature processing on different types of battery data by calling the corresponding configuration rule without classifying the battery data, so that distributed processing can be performed on multiple types of battery data at the same time, and the processing efficiency is improved. Therefore, the feature processing problem of a big data scene is solved, and the reusability and the difference of battery data feature processing are solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a battery data feature processing method, device, platform and storage medium. Background Art

[0002] When processing the existing massive amount of battery data, it is necessary to classify and process them according to different battery types, and it is impossible to process different battery data at the same time. Summary of the invention

[0003] The embodiments of the present invention provide a method, device, platform and storage medium for processing battery data features, aiming to solve the technical problem of differences in processing data of different batteries.

[0004] In a first aspect, an embodiment of the present application proposes a method for processing battery data features, the method comprising:

[0005] Obtaining unprocessed battery data representing the operating condition of the battery;

[0006] Calling corresponding configuration rules based on the battery data to be processed, wherein the configuration rules are used to perform feature processing on the battery data to be processed;

[0007] The battery data to be processed is subjected to feature processing by using the configured rules to obtain a processing result.

[0008] In this embodiment, the battery data to be processed that characterizes the battery operating conditions is obtained; the corresponding configured rules are called based on the battery data to be processed, and the configured rules are used to perform feature processing on the battery data to be processed; the battery data to be processed is feature processed by the configured rules to obtain a processing result, and by calling the corresponding configured rules, different types of battery data are feature processed without classifying the battery data, and multiple types of battery data can be distributedly processed at the same time, thereby solving the feature processing problem in big data scenarios and solving the reusability and diversity of battery data feature processing.

[0009] In some embodiments, the calling of corresponding configuration rules based on the battery data to be processed includes:

[0010] Analyze the battery data to be processed to obtain the type of battery to be processed;

[0011] Determine a processing flow of battery data to be processed based on the type of battery to be processed;

[0012] The corresponding configuration rules are called through the processing flow.

[0013] This embodiment determines the type of battery data to be processed by analyzing the battery data to be processed, and quickly determines the processing flow of different types of battery data to be processed according to the type of battery to be processed. By calling the corresponding configuration rules through the processing flow, different processing flows of different battery data to be processed can be met, thereby realizing customization of different battery data.

[0014] In some embodiments, the calling of the corresponding configuration rule through the processing flow includes:

[0015] In the case where the processing flow is to preprocess the battery data to be processed and calculate features, the preprocessing configuration rule and the feature calculation configuration rule are called.

[0016] In the technical solution of the embodiment of the present application, when the processing flow is to preprocess and calculate features of the battery data to be processed, the configuration rules corresponding to the preprocessing and the configuration rules corresponding to the feature calculation can be directly called to quickly process the battery data to be processed and improve the processing efficiency of the battery data.

[0017] In some embodiments, the step of performing feature processing on the battery data to be processed by using the configured rules to obtain a processing result includes:

[0018] In response to the triggered detection requirement, determining detection parameters based on the detection requirement;

[0019] Selecting a target configuration component from the configuration rules based on the detection parameter;

[0020] The target configuration component performs feature processing on the battery data to be processed to obtain a processing result.

[0021] In the technical solution of the embodiment of the present application, different types of battery data to be processed have different detection requirements, so the detection parameters can be determined according to the detection requirements, so that the corresponding target configuration components can be quickly selected from the configuration rules through the detection parameters, and the features of the battery data to be processed can be quickly processed through the target configuration components, which can flexibly handle the detection requirements of various scenarios and improve the efficiency of battery data processing.

[0022] In some embodiments, before calling the corresponding configuration rule based on the battery data to be processed, the method further includes:

[0023] Obtain battery sample data that characterizes different operating conditions of the battery;

[0024] Analyze the battery sample data to determine the processing logic of the battery sample data;

[0025] Based on the processing logic, component configuration for feature processing is performed to build configuration rules.

[0026] This embodiment collects massive data in advance to obtain battery sample data under different operating conditions of the battery, and analyzes the battery sample data, so as to quickly determine the processing logic that needs to be processed for different battery sample data, thereby performing component configuration for feature processing in advance, building different configuration rules, and statistically summarizing the different configuration rules. Therefore, when performing feature processing on the battery data to be processed, by calling the corresponding configuration rules, the needs of data aggregation in various scenarios can be flexibly handled, and the problem of massive data feature generation in the battery field can be flexibly and efficiently solved.

[0027] In some embodiments, the configurable rules include pre-processing configurable rules;

[0028] The component configuration for feature processing based on the processing logic and the construction of configuration rules include:

[0029] When the processing logic is preprocessing, configuring components required for preprocessing to obtain preprocessing components;

[0030] Preprocessing configuration rules are constructed through the preprocessing component.

[0031] In the technical solution of the embodiment of the present application, when the processing logic of the battery data to be processed is preprocessing, the corresponding components can be directly configured through the preprocessing processing flow to obtain the preprocessing components, and the preprocessing configuration rules can be constructed through the preprocessing components. By establishing the preprocessing configuration rules in advance, when the data to be processed is preprocessed, the preprocessing configuration rules can be directly called. By automatically scheduling the preprocessing process of massive battery data, the efficiency of battery data feature processing can be improved.

[0032] In some embodiments, the preprocessing includes field analysis, and the preprocessing configurable rules include field analysis configurable rules;

[0033] The component configuration for feature processing based on the processing logic and the construction of configuration rules include:

[0034] When the processing logic is field analysis, components required for field analysis are configured to obtain field analysis components;

[0035] The field analysis component is used to construct field analysis configuration rules.

[0036] This embodiment further analyzes the preprocessing process, configures the processing components of the field analysis in the battery data preprocessing, and constructs the field analysis configuration rules, so that when performing field analysis on the data, the field analysis configuration rules are directly called to improve the efficiency of the field analysis of the battery data to be processed.

[0037] In some embodiments, the preprocessing includes data processing, and the preprocessing configurable rules include data processing configurable rules;

[0038] The component configuration for feature processing based on the processing logic and the construction of configuration rules include:

[0039] When the processing logic is data processing, configuring components required for data processing to obtain data processing components;

[0040] Data processing configuration rules are constructed through the data processing components.

[0041] This embodiment further analyzes the preprocessing process, configures the processing components for data processing configuration in battery data preprocessing, and constructs data processing configuration rules, so that when processing battery data, the data processing configuration rules are directly called to improve the efficiency of data processing of the battery data to be processed.

[0042] In some embodiments, the configurable rules include feature computation configurable rules;

[0043] The component configuration for feature processing based on the processing logic and the construction of configuration rules include:

[0044] When the processing logic is feature calculation, components required for feature calculation are configured to obtain feature calculation components;

[0045] The feature calculation configuration rules are constructed through the feature calculation component.

[0046] This embodiment configures the processing components during feature calculation by analyzing the processing flow when performing feature calculation on the battery data to be processed, and constructs feature calculation configuration rules. Therefore, when performing feature calculation on the data to be processed, the feature calculation configuration rules are directly called. Through feature calculation configuration, the differences in battery feature data acquisition in different scenarios are resolved, thereby improving the efficiency of feature calculation on the battery data to be processed.

[0047] In some embodiments, the method further comprises:

[0048] Configure the feature calculation plug-in required for feature calculation;

[0049] The feature calculation plug-in is integrated into the feature calculation configuration rule.

[0050] This embodiment also uses big data components to determine the feature calculation plug-in required for feature calculation. When performing feature calculation, the feature calculation plug-in in the configuration rule is directly called to drive the data feature calculation plug-in to perform distributed calculation. Through feature calculation configuration, the differences in battery feature data acquisition in different scenarios are solved, data feature calculation capabilities are provided for multiple scenarios, and data feature calculation capabilities are expanded.

[0051] In some embodiments, the configuration rules include: field analysis configuration rules, data processing configuration rules, and feature calculation configuration rules;

[0052] The step of performing feature processing on the battery data to be processed by using the configured rules to obtain a processing result includes:

[0053] Performing field analysis on the battery data to be processed by using the field analysis configuration rule to obtain keyword data of the battery data to be processed;

[0054] Performing data processing on the keyword data according to the data processing configuration rule to obtain processed keyword data;

[0055] The processed keyword data is calculated using the feature calculation configuration rules to obtain a processing result.

[0056] This embodiment deploys field analysis configuration rules, data processing configuration rules and feature calculation configuration rules, so that when processing the battery data to be processed, the configured field analysis configuration rules are used to perform field analysis on the battery data to be processed, and keyword data of the battery data to be processed is obtained to accelerate the subsequent processing flow, and data processing is performed on the keyword data through the data processing configuration rules. By reading the configuration in the data processing configuration rules, data processing is performed to obtain processed keyword data, which accelerates the feature calculation of the battery data to be processed, and the processed keyword data is calculated through the feature calculation configuration rules, thereby realizing the calculation of data features for different business scenarios.

[0057] In a second aspect, an embodiment of the present invention further provides a battery data feature processing device, the battery data feature processing device comprising:

[0058] An acquisition module, used to acquire battery data to be processed that characterizes the operating conditions of the battery;

[0059] A calling module, used for calling corresponding configuration rules based on the battery data to be processed, wherein the configuration rules are used for performing feature processing on the battery data to be processed;

[0060] The processing module is used to perform feature processing on the battery data to be processed according to the configured rules to obtain a processing result.

[0061] In a third aspect, an embodiment of the present invention further proposes a battery data feature processing platform, on which the battery data feature processing method as described above is executed.

[0062] In a fourth aspect, an embodiment of the present invention further proposes a storage medium, on which a battery data feature processing program is stored, and when the battery data feature processing program is executed by a processor, the battery data feature processing method as described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0064] Figure 1 This is a schematic diagram of the structure of an embodiment of a battery data feature processing platform proposed in this application;

[0065] Figure 2 A schematic diagram of a flow chart of an embodiment of a method for processing battery data characteristics according to an embodiment of the present invention;

[0066] Figure 3 It is another flowchart of an embodiment of the battery data feature processing method proposed in an embodiment of the present invention;

[0067] Figure 4 It is another flowchart of an embodiment of a method for processing battery data characteristics proposed in an embodiment of the present invention;

[0068] Figure 5 It is another flowchart of an embodiment of the battery data feature processing method proposed in an embodiment of the present invention;

[0069] Figure 6 It is another flowchart of an embodiment of a method for processing battery data characteristics proposed in an embodiment of the present invention;

[0070] Figure 7 It is another flowchart of an embodiment of a method for processing battery data characteristics proposed in an embodiment of the present invention;

[0071] Figure 8 A schematic diagram of a page for performing field analysis configuration in an embodiment of a battery data feature processing method according to an embodiment of the present invention;

[0072] Fig. 9 It is another flowchart of an embodiment of a method for processing battery data characteristics proposed in an embodiment of the present invention;

[0073] Fig.10 A schematic diagram of a page for configuring data processing in an embodiment of a battery data feature processing method according to an embodiment of the present invention;

[0074] Fig.11 A schematic diagram of a page for configuring feature calculation in an embodiment of a method for processing battery data features according to an embodiment of the present invention;

[0075] Fig.12 A schematic diagram of a flow chart of preprocessing battery data to be processed in a battery data feature processing method proposed in an embodiment of the present invention;

[0076] Fig.13 A schematic diagram of a flow chart of a battery data feature processing method proposed in an embodiment of the present invention for performing feature calculation on battery data to be processed;

[0077] Fig.14 This is a schematic diagram of the structure of an embodiment of a battery data feature processing device proposed in an embodiment of the present invention.

[0078] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0079] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0080] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the terms "including" and "having" in the specification and claims of the present invention and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0081] In the description of the embodiments of the present invention, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present invention, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0082] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0083] In the description of the embodiments of the present invention, the term "and / or" is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0084] In the description of the embodiments of the present invention, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0085] In the description of the embodiments of the present invention, the technical terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the embodiments of the present invention.

[0086] In the description of the embodiments of the present invention, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific circumstances.

[0087] At present, when testing power batteries, massive amounts of data in different scenarios can be collected for feature processing, thereby realizing the detection of power batteries.

[0088] However, there are certain differences in the feature processing of battery data in different scenarios. If you want to perform feature processing on battery data in different scenarios at the same time, you need to deploy multiple processing methods at the same time or use one processing method to perform feature processing on one type of battery data, and then continuously update the processing logic and processing parameters to perform feature processing on the battery data of other scenarios. It is impossible to perform feature processing of massive data at the same time, which leads to the uniformity and differences in the processing process.

[0089] In order to solve the above-mentioned defects, the inventive concept of the present application is as follows:

[0090] The differences in battery data in multiple scenarios are resolved through data access configuration rules. By configuring the processing flows of the battery data to be processed, the processing requirements of different data in different scenarios can be flexibly handled, the efficiency of feature processing can be improved, and the problem of feature processing of massive data in the battery field can be flexibly and efficiently resolved.

[0091] Based on the above considerations, in order to solve the reusability and diversity of battery data processing, after in-depth research, a battery data feature processing method, device, platform and storage medium are proposed, which are suitable for various scenarios of battery data feature processing during the actual use of the battery, for example, in the specific application scenario of safety monitoring of batteries of equipment such as electric vehicles, ships or aircraft during driving or charging.

[0092] In order to better understand the embodiments of the present application, the battery data feature processing method, device, platform and storage medium provided according to the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0093] The execution subject of the battery data feature processing method provided in the embodiment of the present application can be a battery data feature processing platform, which can be used for feature processing of massive battery data. The battery data feature processing platform is embedded with a module for storing configuration rules, so that when the battery data to be processed is subjected to feature processing, the corresponding configuration rules can be called to perform feature processing on the battery data to be processed. The configuration rules include field configuration rules, data processing configuration rules, and feature calculation configuration rules, and can also include other configuration rules, which can be added according to the processing requirements of the battery data to be processed.

[0094] For the sake of convenience, here we use Figure 1 The battery data feature processing platform shown serves as a specific application environment of the battery data feature processing method provided in this embodiment. The battery data feature processing platform is only a possible example, and does not limit the specific application environment of the battery data feature processing method provided in the embodiment of the present application. The battery data feature processing method provided in the embodiment of the present application can also be applied to other battery data feature processing platforms.

[0095] like Figure 1 As shown, the battery data feature processing platform is provided with a data preprocessing module and a data feature calculation module. The data preprocessing module is used to perform data preprocessing on the battery data to be processed, which may include field analysis processing and data processing. The data feature calculation module is used to perform feature calculation on the battery data to be processed. When preprocessing the battery data to be processed, the data preprocessing module interacts with the module storing the configuration rules, and calls the field configuration rules and the data processing configuration rules to preprocess the battery data to be processed. When performing feature calculation on the battery data to be processed or the preprocessed battery data, the data feature calculation module calls the feature calculation configuration rules to perform feature calculation on the battery data to be processed or the preprocessed battery data, thereby obtaining the feature calculation result. The feature calculation configuration rules in the configuration module also incorporate feature calculation plug-ins, so that when performing feature calculation on the data, the feature calculation plug-ins can be called to perform feature calculation. The feature calculation plug-ins can also be stored in the feature calculation plug-in library. The battery data feature processing platform can also embed the feature calculation plug-in library, so that when performing feature calculation on the data, the corresponding feature calculation plug-ins in the feature calculation plug-in library are directly called to perform feature calculation. Therefore, by preprocessing and feature calculation of the battery data to be processed, data feature processing capabilities are provided for various scenarios, solving the reusability and differences of battery data in various scenarios.

[0096] In some embodiments of the present invention, reference Figure 2 The embodiment of the present invention proposes a method for processing battery data features. The method for processing battery data features may include:

[0097] Step S10: Obtaining battery data to be processed that characterizes the battery operating condition.

[0098] It should be understood that the battery operating conditions may include battery charging and discharging conditions or other conditions, and the corresponding battery operating conditions may be obtained, and the battery data to be processed that characterizes the battery operating conditions may be collected. The battery data to be processed may include battery configuration data, battery voltage and current data, etc., and may also include other data, which is not limited in this embodiment.

[0099] Step S20: calling corresponding configuration rules based on the battery data to be processed, where the configuration rules are used to perform feature processing on the battery data to be processed.

[0100] It should be noted that the battery data to be processed can be analyzed to determine the process that needs to be processed for the battery data to be processed, and then the corresponding configured rules can be called according to the process, so that the features of the battery data to be processed can be processed through the configured rules.

[0101] Different configuration rules can be constructed and summarized in advance, and the configuration rules can be constructed based on the analysis of different types of battery sample data collected in advance. For example, the configuration rules include pre-processing configuration rules and feature calculation configuration rules.

[0102] The processing flow of the battery data to be processed can be determined according to the type of the battery data to be processed uploaded by the user. For example, if the type of the battery data to be processed is the configuration data of the battery data to be processed, then the processing flow of the battery data to be processed can be determined to be preprocessing the configuration data, and the preprocessing configuration rules can be called to preprocess the battery data to be processed through the preprocessing configuration rules. For example, if the type of the battery data to be processed is the voltage data of the battery data to be processed, then the processing flow of the battery data to be processed can be determined to be preprocessing the voltage data first, and then performing feature calculation on the preprocessed voltage data, and the preprocessing configuration rules and feature calculation configuration rules can be called.

[0103] When the corresponding configuration rules are called, feature processing can be performed on the battery data to be processed through the corresponding configuration rules.

[0104] Step S30: Perform feature processing on the battery data to be processed by using the configured rules to obtain a processing result.

[0105] It should be understood that feature processing may include any one or both of preprocessing and feature calculation, and may also include other processing methods, which are not limited in this embodiment. This embodiment is described by taking preprocessing and / or feature calculation as an example.

[0106] After the corresponding configuration rules are obtained, the battery data to be processed can be feature processed by the configuration rules to obtain the processing results. For example, if the configuration rules are preprocessing configuration rules, the battery data to be processed can be preprocessed by the preprocessing configuration rules to obtain the preprocessing results.

[0107] This embodiment obtains the pending battery data that characterizes the battery operating conditions; based on the pending battery data, the corresponding configured rules are called, and the configured rules are used to perform feature processing on the pending battery data; the feature processing is performed on the pending battery data through the configured rules to obtain a processing result, and by calling the corresponding configured rules, feature processing is performed on different types of battery data without classifying the battery data, and multiple types of battery data can be distributedly processed at the same time, thereby solving the feature processing problem in big data scenarios and solving the reusability and diversity of battery data feature processing.

[0108] In some embodiments, since the corresponding configuration rules can be quickly determined by analyzing the battery data to be processed, referring to Figure 3 , step S20 specifically includes:

[0109] Step S201: Analyze the battery data to be processed to obtain the type of the battery to be processed.

[0110] It should be noted that the battery type of each battery to be processed can be determined by analyzing the battery data to be processed to determine how many types of batteries there are in the battery data to be processed, and then the battery type can be determined according to the battery data to be processed. For example, the battery types include oxide batteries, lithium-ion batteries, sodium-ion batteries, etc.

[0111] As an example, the type of the battery to be processed may also be directly obtained, for example, the battery data to be processed carries various battery types.

[0112] Step S202: Determine a processing flow of the battery data to be processed based on the type of the battery to be processed.

[0113] It is understandable that, since the processing procedures of different types of battery data may be different, after the type of battery to be processed is obtained, the processing procedure of the battery data to be processed can be determined by the type of battery to be processed.

[0114] Step S203: calling corresponding configuration rules through the processing flow.

[0115] As an example, after obtaining the processing flow of the battery data to be processed, the corresponding configuration rules can be called through the processing flow. For example, if the processing flow is to preprocess the battery data to be processed, the preprocessing configuration rules are called. If the processing flow is to preprocess the data to be processed and calculate features, the preprocessing configuration rules and feature calculation configuration rules are called.

[0116] This embodiment determines the type of battery data to be processed by analyzing the battery data to be processed, and quickly determines the processing flow of different types of battery data to be processed according to the type of battery to be processed. By calling the corresponding configuration rules through the processing flow, different processing flows of different battery data to be processed can be met, thereby realizing customization of different battery data.

[0117] In some embodiments, due to different processing flows, the configured rules called are also different, so the step of "calling the corresponding configured rules through the processing flow" includes:

[0118] When the processing flow is to pre-process the battery data to be processed and calculate the characteristics, the pre-processing configuration rule and the characteristic calculation configuration rule are called.

[0119] It should be understood that when the processing flow is to preprocess and calculate the characteristics of the battery data to be processed, the preprocessing configuration rules and the characteristic calculation configuration rules can be called. The preprocessing configuration rules are applicable to the data preprocessing module, and the data characteristic calculation configuration rules are applicable to the characteristic calculation module. The preprocessing process and the characteristic calculation process of the battery data to be processed can be carried out simultaneously, and the processing order can also be set. For example, the battery data to be processed is preprocessed first to obtain the preprocessing result, and then the characteristic calculation is performed on the preprocessing result to obtain the final processing result. The specific processing method can be set according to different processing requirements.

[0120] For example, the processing order is to preprocess the battery data to be processed first, and then perform feature calculation on the battery data to be processed. The result of the preprocessing output is used as the input of the feature calculation, so that the preprocessing configuration rules can be used in the data preprocessing module to preprocess the battery data to obtain the preprocessing result, and the feature calculation configuration rules can be used in the data feature calculation module to perform feature calculation on the preprocessing result to obtain the final processing result.

[0121] In the technical solution of the embodiment of the present application, when the processing flow is to preprocess and calculate features of the battery data to be processed, the configuration rules corresponding to the preprocessing and the configuration rules corresponding to the feature calculation can be directly called to quickly process the battery data to be processed and improve the processing efficiency of the battery data.

[0122] In some embodiments, due to different detection requirements, the obtained battery data to be processed is also different. Therefore, the specific detection requirements can be determined according to the obtained battery data to be processed, so as to select the corresponding configuration component to perform feature processing on the battery data to be processed. Figure 4 , step S30 specifically includes:

[0123] Step S301: In response to a triggered detection requirement, a detection parameter is determined based on the detection requirement.

[0124] It should be noted that different detection requirements require different detection methods, and the methods of processing the battery data to be processed are also different. Therefore, the detection parameters can be determined in response to the triggered detection requirements. The detection requirements can be generated by the user using the components selected on the battery data feature processing platform. For example, if the triggered detection requirement is to perform feature processing on the battery voltage based on the battery data to be processed, then the detection requirement is to detect the battery voltage, and the detection parameters are the voltage-related parameters in the battery data to be processed, such as the voltage value.

[0125] Step S302: Select a target configuration component from the configuration rules based on the detection parameters.

[0126] It should be understood that multiple configuration components are embedded in the configuration rules, and different detection parameters require different configuration components. The configuration components can be used to perform feature processing on the battery data to be processed. For example, if the detection parameter is a voltage-related parameter, the configuration rules include preprocessing configuration rules and feature calculation configuration rules. The voltage preprocessing configuration component is selected from the preprocessing configuration rules and the voltage feature calculation configuration component is selected from the feature calculation configuration rules, that is, the target configuration components are the voltage preprocessing configuration component and the voltage feature calculation configuration component.

[0127] Step S303: Perform feature processing on the battery data to be processed according to the target configuration component to obtain a processing result.

[0128] In a specific implementation, after the target configuration component is determined, the target configuration component can be used to perform feature processing on the battery data to be processed, thereby obtaining a processing result. For example, the target configuration component is a voltage feature calculation configuration component, and the voltage feature calculation configuration component may include a voltage outlier calculation configuration component, so that the voltage outlier calculation configuration component is used to perform voltage outlier calculation on the battery data to be processed, and obtain a voltage outlier calculation result.

[0129] In the technical solution of the embodiment of the present application, different types of battery data to be processed have different detection requirements, so the detection parameters can be determined according to the detection requirements, so that the corresponding target configuration components can be quickly selected from the configuration rules through the detection parameters, and the features of the battery data to be processed can be quickly processed through the target configuration components, which can flexibly handle the detection requirements of various scenarios and improve the efficiency of battery data processing.

[0130] In some embodiments, the configuration rules are constructed in advance. When the battery data to be processed is subjected to feature processing, the corresponding configuration rules can be directly called to improve the efficiency of feature processing. Before step S20, a step of constructing configuration rules is also included, such as Figure 5 As shown, the steps of constructing the configuration rules may include:

[0131] Step S11: obtaining battery sample data representing different operating conditions of the battery;

[0132] Step S12: Analyze the battery sample data and determine the processing logic of the battery sample data;

[0133] Step S13: Configure components for feature processing based on processing logic and construct configuration rules.

[0134] It should be noted that the battery sample data is a large amount of battery data collected in advance, including battery data in different scenarios. The processing logic of the battery sample data can be determined by analyzing the battery sample data. The processing logic of the battery sample data may include the processing flow and processing sequence of the battery data in the battery sample data. For example, the processing logic is to preprocess the battery data and calculate the features. The processing sequence is to preprocess the battery data first, and then calculate the features based on the preprocessing results.

[0135] After obtaining the processing logic, the components for feature processing can be configured through the processing logic to obtain a variety of configuration rules. The configuration rules can be stored in a configuration library. For example, a configuration library is provided in the configuration module, and a variety of different types of configuration rules are stored in the configuration library. When feature processing of battery data is required, the corresponding configuration rule is called from the configuration library.

[0136] This embodiment collects massive data in advance to obtain battery sample data under different operating conditions of the battery, and analyzes the battery sample data, so as to quickly determine the processing logic that needs to be processed for different battery sample data, thereby performing component configuration for feature processing in advance and building different configuration rules. When performing feature processing on the battery data to be processed, by calling the corresponding configuration rules, the needs of data aggregation in various scenarios can be flexibly handled, and the problem of massive data feature generation in the battery field can be flexibly and efficiently solved.

[0137] In some embodiments, the configuration rules include preprocessing configuration rules. The preprocessing configuration rules can be constructed in advance so that when preprocessing the battery data to be processed, the preprocessing configuration rules can be directly called to perform preprocessing, thereby improving the efficiency of preprocessing.

[0138] Alternatively, if Figure 6 As shown, the steps of constructing the configuration rules for component configuration based on the processing logic for feature processing include:

[0139] Step S131: when the processing logic is preprocessing, configure components required for preprocessing to obtain preprocessing components.

[0140] It should be noted that when the processing logic is preprocessing, the method of preprocessing the battery sample data can be collected in advance, so as to configure the components required for preprocessing and obtain the preprocessing components. The preprocessing components may include components for extracting keywords from the data, components for data processing, etc.

[0141] Step S132: construct preprocessing configuration rules through preprocessing components.

[0142] Preprocessing components are aggregated to form preprocessing configuration rules.

[0143] In the technical solution of the embodiment of the present application, when the processing logic of the battery data to be processed is preprocessing, the corresponding components can be directly configured through the preprocessing processing flow to obtain the preprocessing components, and the preprocessing configuration rules can be constructed through the preprocessing components. By establishing the preprocessing configuration rules in advance, when the data to be processed is preprocessed, the preprocessing configuration rules can be directly called. By automatically scheduling the preprocessing process of massive battery data, the efficiency of battery data feature processing can be improved.

[0144] In some embodiments, the preprocessing includes field analysis, and the preprocessing configurable rules include field analysis configurable rules;

[0145] like Figure 7 As shown, the steps of constructing the configuration rules for component configuration based on the processing logic for feature processing include:

[0146] Step S131 ′: when the processing logic is field analysis, components required for field analysis are configured to obtain field analysis components.

[0147] Step S132': construct field analysis configuration rules through field analysis components.

[0148] When the processing logic is to perform field analysis on data, the methods of performing field analysis, such as keyword extraction, field splicing, etc., can be collected, so as to configure the components of field analysis according to the methods of performing field analysis, thereby obtaining field analysis components, and using all field analysis components as field analysis configuration rules.

[0149] like Figure 8 As shown, Figure 8 A schematic diagram of a page for configuring field analysis. For example, if the field analysis method is keyword extraction, keyword extraction components can be configured, including voltage field components, current field components, temperature components, SOC field components, etc., so as to construct field analysis configuration rules.

[0150] For example, if the detection parameter of the battery data to be processed is a voltage detection parameter, the voltage field component in the field analysis configuration rule is called to perform keyword extraction on the voltage parameter through the voltage field component.

[0151] This embodiment further analyzes the preprocessing process, configures the processing components of the field analysis in the battery data preprocessing, and constructs the field analysis configuration rules, so that when performing field analysis on the data, the field analysis configuration rules are directly called to improve the efficiency of the field analysis of the battery data to be processed.

[0152] In some embodiments, preprocessing includes data processing, and the preprocessing configurable rules include data processing configurable rules;

[0153] like Fig. 9 As shown, the steps of constructing the configuration rules for component configuration based on the processing logic for feature processing include:

[0154] Step S131": when the processing logic is data processing, configure the components required for data processing to obtain data processing components; and construct data processing configuration rules through the data processing components.

[0155] When the processing logic is to process data, methods of data processing can be collected, such as data cleaning, data normalization, image data grayscale processing, data calculation, etc., so as to configure components for data processing according to the data processing methods, thereby obtaining data processing components, and using all data processing components as data processing configuration rules.

[0156] like Fig.10 As shown, Fig.10 A schematic diagram of a page for configuring data processing. For example, if the data processing method is data calculation, the data calculation components can be configured, including the sum field, the maximum value field, the mean field, and the variance field, so as to construct data processing configuration rules.

[0157] For example, if the detection parameter of the battery data to be processed is a voltage detection parameter, the summation field component in the data processing configuration rule can be called to sum the voltage of the voltage parameter through the summation field component.

[0158] This embodiment further analyzes the preprocessing process, configures the processing components for data processing configuration in battery data preprocessing, and constructs data processing configuration rules, so that when processing battery data, the data processing configuration rules are directly called to improve the efficiency of data processing of the battery data to be processed.

[0159] In some embodiments, the configurable rules include feature calculation configurable rules;

[0160] The steps of building configuration rules for component configuration based on processing logic for feature processing include:

[0161] When the processing logic is feature calculation, components required for feature calculation are configured to obtain feature calculation components; and feature calculation configuration rules are constructed through the feature calculation components.

[0162] When the processing logic is to perform feature calculation on data, the way of performing feature calculation can be collected, such as voltage outlier calculation, temperature rise anomaly calculation, etc., so as to configure the components of feature calculation according to the way of performing feature calculation, obtain feature calculation components, and use all feature calculation components as feature calculation configuration rules.

[0163] like Fig.11 As shown, Fig.11 A schematic diagram of a page for configuring feature calculation. For example, if the feature calculation processing method is basic feature calculation, a basic feature selection component, a feature calculation method selection component, and a feature calculation parameter component can be configured. The basic feature selection component includes mean, variance, standard deviation, etc. The feature calculation method selection component includes voltage outliers, temperature rise anomalies, etc. The feature calculation parameter component includes feature calculation parameter component 1 and feature calculation parameter component 2, and is configured with threshold 1 and threshold 2, etc.

[0164] For example, if the detection parameter of the battery data to be processed is a voltage detection parameter, the mean component in the feature calculation configuration rule can be called to perform voltage outlier calculation on the voltage parameter through the mean component.

[0165] This embodiment configures the processing components during feature calculation by analyzing the processing flow when performing feature calculation on the battery data to be processed, and constructs feature calculation configuration rules. Therefore, when performing feature calculation on the data to be processed, the feature calculation configuration rules are directly called. Through feature calculation configuration, the differences in battery feature data acquisition in different scenarios are resolved, thereby improving the efficiency of feature calculation on the battery data to be processed.

[0166] In some embodiments, the method further comprises:

[0167] Configure the feature calculation plug-in required for feature calculation; integrate the feature calculation plug-in into the feature calculation configuration rule.

[0168] Feature calculation plug-ins can be stored in the data feature calculation plug-in library. By calling the feature calculation plug-in required for feature calculation in the data feature calculation plug-in library in advance and configuring the feature calculation plug-in, the feature calculation plug-in can be integrated into the feature calculation configuration rules. The data feature calculation plug-in library includes mean calculation plug-in, variance calculation plug-in, voltage outlier plug-in, and temperature rise anomaly plug-in, etc. Feature calculation plug-ins can also be added according to needs.

[0169] Therefore, when performing feature calculation, in addition to calling the feature calculation components in the feature calculation configuration rules, you can also call the feature calculation plug-ins in the feature calculation configuration rules, so as to add feature calculation logic in the form of plug-ins, which is convenient for expanding data feature calculation capabilities in more scenarios.

[0170] This embodiment also uses big data components to determine the feature calculation plug-in required for feature calculation. When performing feature calculation, the feature calculation plug-in in the configuration rule is directly called to drive the data feature calculation plug-in to perform distributed calculation. Through feature calculation configuration, the differences in battery feature data acquisition in different scenarios are solved, data feature calculation capabilities are provided for multiple scenarios, and data feature calculation capabilities are expanded.

[0171] In some embodiments, the configuration rules include: field analysis configuration rules, data processing configuration rules, and feature calculation configuration rules;

[0172] The battery data to be processed is processed by configuring rules to obtain the following processing results:

[0173] Perform field analysis on the battery data to be processed through field analysis configuration rules to obtain keyword data of the battery data to be processed;

[0174] Performing data processing on keyword data through data processing configuration rules to obtain processed keyword data;

[0175] The processed keyword data is calculated through feature calculation configuration rules to obtain the processing results.

[0176] When the processing flow of the battery data to be processed includes field analysis, data processing and feature calculation, the configuration rules are determined to include field analysis configuration rules, data processing configuration rules and feature calculation configuration rules. The order of feature processing is to first perform field analysis on the battery data to be processed through the field analysis configuration rules to obtain keyword data of the battery data to be processed, and then perform data processing on the keyword data through the data processing configuration rules to obtain processed keyword data, and then perform feature calculation on the processed keyword data through the feature calculation configuration rules to obtain processing results.

[0177] like Fig.12 As shown, Fig.12 The flowchart of preprocessing the battery data to be processed is as follows: by calling the field analysis configuration rule, reading the configured field analysis component, performing field analysis of the data through the field analysis component, calling the data processing configuration rule, reading the configured data processing component, and performing data processing through the data processing component, the preprocessing result is obtained, and the preprocessing result is input into the data feature calculation module to facilitate the subsequent feature calculation process.

[0178] like Fig.13 As shown, Fig.13 The figure is a flow chart of feature calculation for the battery data to be processed. The feature calculation is performed on the preprocessing result by calling the corresponding components in the feature calculation configuration rules and the data feature calculation plug-in library to obtain the final processing result.

[0179] This embodiment deploys field analysis configuration rules, data processing configuration rules and feature calculation configuration rules, so that when processing the battery data to be processed, the configured field analysis configuration rules are used to perform field analysis on the battery data to be processed, and keyword data of the battery data to be processed is obtained to accelerate the subsequent processing flow, and data processing is performed on the keyword data through the data processing configuration rules. By reading the configuration in the data processing configuration rules, data processing is performed to obtain processed keyword data, which accelerates the feature calculation of the battery data to be processed, and the processed keyword data is calculated through the feature calculation configuration rules, thereby realizing the calculation of data features for different business scenarios.

[0180] To achieve the above purpose, the present invention further provides a battery data feature processing device. Fig.14 The structure diagram of an embodiment of a battery data feature processing device provided in an embodiment of the present application is shown, and the battery data feature processing device includes:

[0181] The acquisition module 10 is used to acquire the battery data to be processed that represents the battery operating condition.

[0182] The calling module 20 is used to call the corresponding configuration rules based on the battery data to be processed, and the configuration rules are used to perform feature processing on the battery data to be processed.

[0183] The processing module 30 is used to perform feature processing on the battery data to be processed according to the configured rules to obtain a processing result.

[0184] This embodiment obtains the pending battery data that characterizes the battery operating conditions; based on the pending battery data, the corresponding configured rules are called, and the configured rules are used to perform feature processing on the pending battery data; the feature processing is performed on the pending battery data through the configured rules to obtain a processing result, and by calling the corresponding configured rules, feature processing is performed on different types of battery data without classifying the battery data, and multiple types of battery data can be distributedly processed at the same time, thereby solving the feature processing problem in big data scenarios and solving the reusability and diversity of battery data feature processing.

[0185] In one embodiment, the calling module 20 is further used to analyze the battery data to be processed to obtain the type of the battery to be processed; determine the processing flow of the battery data to be processed based on the type of the battery to be processed; and call the corresponding configuration rules through the processing flow.

[0186] In one embodiment, the calling module 20 is further used to call the preprocessing configuration rules and the feature calculation configuration rules when the processing flow is to preprocess the battery data to be processed and calculate the features.

[0187] In one embodiment, the processing module 30 is also used to respond to the triggered detection requirements and determine the detection parameters based on the detection requirements; select the target configuration components from the configuration rules based on the detection parameters; perform feature processing on the battery data to be processed according to the target configuration components to obtain the processing results.

[0188] In one embodiment, the calling module 20 is also used to obtain battery sample data characterizing different operating conditions of the battery; analyze the battery sample data to determine the processing logic of the battery sample data; configure components for feature processing based on the processing logic to construct configuration rules.

[0189] In one embodiment, the configuration rules include preprocessing configuration rules, and the calling module 20 is also used to configure the components required for preprocessing when the processing logic is preprocessing to obtain preprocessing components; and construct the preprocessing configuration rules through the preprocessing components.

[0190] In one embodiment, preprocessing includes field analysis, and preprocessing configuration rules include field analysis configuration rules; calling module 20 is also used to configure components required for field analysis when the processing logic is field analysis, and obtain field analysis components; field analysis configuration rules are constructed through field analysis components.

[0191] In one embodiment, preprocessing includes data processing, and preprocessing configuration rules include data processing configuration rules; the calling module 20 is also used to configure the components required for data processing when the processing logic is data processing, and obtain the data processing components; the data processing configuration rules are constructed through the data processing components.

[0192] In one embodiment, the configuration rules include feature calculation configuration rules; the calling module 20 is also used to configure the components required for feature calculation when the processing logic is feature calculation, and obtain feature calculation components; the feature calculation configuration rules are constructed through the feature calculation components.

[0193] In one embodiment, the calling module 20 is further used to configure a feature calculation plug-in required for feature calculation; and integrate the feature calculation plug-in into the feature calculation configuration rule.

[0194] In one embodiment, the configuration rules include: field analysis configuration rules, data processing configuration rules and feature calculation configuration rules; the processing module 30 is also used to perform field analysis on the battery data to be processed through the field analysis configuration rules to obtain keyword data of the battery data to be processed; perform data processing on the keyword data through the data processing configuration rules to obtain processed keyword data; calculate the processed keyword data through the feature calculation configuration rules to obtain a processing result.

[0195] To achieve the above objectives, an embodiment of the present invention further provides a battery data feature processing platform, on which the battery data feature processing method as described above is executed.

[0196] To achieve the above objective, an embodiment of the present invention further provides a storage medium, on which a battery data feature processing program is stored. When the battery data feature processing program is executed by a processor, the battery data feature processing method as described above is implemented.

[0197] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0198] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A battery data feature processing method, characterized in that: The battery data feature processing method comprises: Obtaining battery data to be processed that characterizes the operating condition of the battery; Calling corresponding configuration rules based on the battery data to be processed, wherein the configuration rules are used to perform feature processing on the battery data to be processed; The battery data to be processed is subjected to feature processing by using the configured rules to obtain a processing result.

2. The battery data feature processing method according to claim 1, characterized in that: The calling of the corresponding configuration rule based on the battery data to be processed includes: Analyze the battery data to be processed to obtain the type of battery to be processed; Determine a processing flow of battery data to be processed based on the type of battery to be processed; The corresponding configuration rules are called through the processing flow.

3. The battery data feature processing method according to claim 2, characterized in that: The calling of the corresponding configuration rule through the processing flow includes: In the case where the processing flow is to preprocess the battery data to be processed and calculate features, the preprocessing configuration rule and the feature calculation configuration rule are called.

4. The battery data feature processing method according to any one of claims 1 to 3, characterized in that: The step of performing feature processing on the battery data to be processed by using the configured rules to obtain a processing result includes: In response to the triggered detection requirement, determining detection parameters based on the detection requirement; Selecting a target configuration component from the configuration rules based on the detection parameter; The target configuration component performs feature processing on the battery data to be processed to obtain a processing result.

5. The battery data feature processing method according to any one of claims 1 to 4, characterized in that: Before calling the corresponding configuration rule based on the battery data to be processed, the method further includes: Obtain battery sample data that characterizes different operating conditions of the battery; Analyze the battery sample data to determine the processing logic of the battery sample data; Based on the processing logic, component configuration for feature processing is performed to build configuration rules.

6. The battery data feature processing method according to claim 5, characterized in that: The configuration rules include pre-processing configuration rules; The component configuration for feature processing based on the processing logic and the construction of configuration rules include: When the processing logic is preprocessing, configuring components required for preprocessing to obtain preprocessing components; Preprocessing configuration rules are constructed through the preprocessing component.

7. The battery data feature processing method according to claim 6, characterized in that: The preprocessing includes field analysis, and the preprocessing configuration rules include field analysis configuration rules; The component configuration for feature processing based on the processing logic and the construction of configuration rules include: When the processing logic is field analysis, components required for field analysis are configured to obtain field analysis components; The field analysis component is used to construct field analysis configuration rules.

8. The battery data feature processing method according to claim 6, characterized in that: The preprocessing includes data processing, and the preprocessing configuration rules include data processing configuration rules; The component configuration for feature processing based on the processing logic and the construction of configuration rules include: When the processing logic is data processing, configuring components required for data processing to obtain data processing components; Data processing configuration rules are constructed through the data processing components.

9. The battery data feature processing method according to claim 5, characterized in that: The configuration rules include feature calculation configuration rules; The component configuration for feature processing based on the processing logic and the construction of configuration rules include: When the processing logic is feature calculation, components required for feature calculation are configured to obtain feature calculation components; The feature calculation configuration rules are constructed through the feature calculation component.

10. The battery data feature processing method according to claim 9, characterized in that: The method further comprises: Configure the feature calculation plug-in required for feature calculation; The feature calculation plug-in is integrated into the feature calculation configuration rule.

11. The battery data feature processing method according to any one of claims 1 to 10, characterized in that: The configuration rules include: field analysis configuration rules, data processing configuration rules and feature calculation configuration rules; The step of performing feature processing on the battery data to be processed by using the configured rules to obtain a processing result includes: Performing field analysis on the battery data to be processed by using the field analysis configuration rule to obtain keyword data of the battery data to be processed; Performing data processing on the keyword data according to the data processing configuration rule to obtain processed keyword data; The processed keyword data is calculated using the feature calculation configuration rules to obtain a processing result.

12. A battery data feature processing device, characterized in that: The battery data feature processing device comprises: An acquisition module, used to acquire battery data to be processed that characterizes the operating conditions of the battery; A calling module, used for calling corresponding configuration rules based on the battery data to be processed, wherein the configuration rules are used for performing feature processing on the battery data to be processed; The processing module is used to perform feature processing on the battery data to be processed according to the configured rules to obtain a processing result.

13. A battery data feature processing platform, characterized in that: The battery data feature processing platform executes the battery data feature processing method as described in any one of claims 1 to 12.

14. A storage medium, characterized in that: The storage medium stores a battery data feature processing program, and when the battery data feature processing program is executed by the processor, the battery data feature processing method according to any one of claims 1 to 12 is implemented.

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